An Efficient Wireless Power Transfer System to Balance the State of Charge of Electric Vehicles

Sarker, Ankur; Qiu, Chenxi; Shen, Haiying; Gil, Andrea; Taiber, Joachim; Chowdhury, Mashrur; Martin, Jim; Devine, Mac; Rindos, AJ

doi:10.1109/icpp.2016.44

Cited by 19 publications

(6 citation statements)

References 24 publications

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“…The proof for P(D n < x|E 8,4,1 , E 8,3,1 , E 8,2,5 , E 8,1,3 , E 8 ) is similar to that ofP(D n < x|E 7,4,1 , E 7,3,3 , E 7,2,5 , E 7,1,3 , E 7 )given in(41).• Event E 8,4,2 : Description: If we take the nearest vertical charging road;Event L 8,7 = E 8,4,2 ∩ E 8,3,1 ∩ E 8,2,5 ∩ E 8,1,3 ∩ E 8 ; Probability: P(E 8,4,2 |E 8,3,1 |E 8,2,5 , E 8,1,3 , E 8 ) = dv 0 F X1 (x)f DN−HC(x) dx; P(L 8,7 ) = P(E 8,4,2 |E 8,3,1 , E 8,2,5 , E 8,1,3 , E 8 ) × P(E 8,3,1 |E 8,2,5 , E 8,1,3 , E 8 ) × P(E 8,2,5 |E 8,1,3 , E 8 )P(E 8,1,3 |E 8 )P(E 8 ); P(D n < x|L 8,7 ) = P(D n < x|E 8,4,2 , E 8,3,1 , E 8,2,5 , E 8,1,3…”

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confidence: 69%

“…Fundamental principles of wireless charging using magnetic field resonance, designs of resonant magnetic coils, and electromagnetic field noise suppression methods are introduced in [40]. The problem of allocating power from charging lanes to in-motion EVs is distance between the nearest vertical non-charging road and the nearest vertical charging road from source X 2 distance between the nearest horizontal non-charging road and the nearest horizontal charging road from source d L distance from source to the nearest horizontal road in the opposite direction of the destination T c event that a given trip passes through at least one charging road T c event that a given trip passes through no charging roads initially studied in [41] by balancing the state of charge of EVs. Later, a solution to allocating power to EVs, enabling them to arrive at destinations while achieving goals such as balancing the state of charge and power stored in EVs, or minimizing the total power charged, is addressed using a greedy approach in [42].…”

Section: A Wireless Charging For Electric Vehiclesmentioning

confidence: 99%

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Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach

Nguyen

Kishk

Alouini

2021

IEEE Open J. Veh. Technol.

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With the increasing demand for greener and more energy efficient transportation solutions, electric vehicles (EVs) have emerged to be the future of transportation across the globe. However, currently, one of the biggest bottlenecks of EVs is the battery. Small batteries limit the EVs driving range, while big batteries are expensive and not environmentally friendly. One potential solution to this challenge is the deployment of charging roads, i.e., dynamic wireless charging systems installed under the roads that enable EVs to be charged while driving. In this paper, we use tools from stochastic geometry to establish a framework that enables evaluating the performance of charging roads deployment in metropolitan cities. We first present the course of actions that a driver should take when driving from a random source to a random destination in order to maximize dynamic charging during the trip. Next, we analyze the distribution of the distance to the nearest charging road. This distribution is vital for studying multiple performance metrics such as the trip efficiency, which we define as the fraction of the total trip spent on charging roads. Next, we derive the probability that a given trip passes through at least one charging road. The derived probability distributions can be used to assist urban planners and policy makers in designing the deployment plans of dynamic wireless charging systems. In addition, they can also be used by drivers and automobile manufacturers in choosing the best driving routes given the road conditions and level of energy of EV battery.

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confidence: 69%

Section: A Wireless Charging For Electric Vehiclesmentioning

confidence: 99%

Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach

Nguyen

Kishk

Alouini

2021

IEEE Open J. Veh. Technol.

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“…where E start and E end is the energy of the battery (KWh) before and after traversing the road segment respectively and E cap is the battery energy capacity. We follow the computation of the battery energy given by [58]. We, however, assume that the velocity of an EV is constant while traversing the road segment.…”

Section: 2mentioning

confidence: 99%

“…An analysis on the effectiveness of placing wireless charging units at traffic intersections in order to take advantage of the frequent stops at these locations is taken in [50] . Methods on how to effectively distribute power to the different charging coils along a wireless charging lane in a vehicle-to-infrastructure (V2I) communication system have also be demonstrated [58]. The authors in [32] carry out simulations over a traffic network to show how connected vehicle technology, such as vehicle-to-vehicle (V2V) or V2I communications can be utilized in order effectively facilitate the EV charging process at fast-charging stations.…”

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confidence: 99%

Optimal Placement of wireless charging lanes in road networks

Ushijima‐Mwesigwa¹,

Khan²,

Chowdhury³

et al. 2021

Journal of Industrial &Amp; Management Optimization

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The emergence of electric vehicle wireless charging technology, where a whole lane can be turned into a charging infrastructure, leads to new challenges in the design and analysis of road networks. From a network perspective, a major challenge is determining the most important nodes with respect to the placement of the wireless charging lanes. In other words, given a limited budget, cities could face the decision problem of where to place these wireless charging lanes. With a heavy price tag, a placement without a careful study can lead to inefficient use of limited resources. In this work, the placement of wireless charging lanes is modeled as an integer programming problem. The basic formulation is used as a building block for different realistic scenarios. We carry out experiments using real geospatial data and compare our results to different network-based heuristics. Reproducibility: all datasets, algorithm implementations and mathematical programming formulation presented in this work are available at https://github.com/hmwesigwa/smartcities.git

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“…Recent studies focus on energy optimization of EVs (Bhavsar, He, Chowdhury, Fries, & Shealy, ; He, Chowdhury, Pisu, & Ma, ) and ITS technologies to facilitate smart charging of EVs (Johnson, Chowdhury, He, & Taiber, , ; Sarkar et al., ). Deflorio, Guglielmi, Pinna, Castello, and Marfull () develop a design framework for EV charging infrastructure based on the WCU performance.…”

Section: Literature Reviewmentioning

confidence: 99%

Wireless charging utility maximization and intersection control delay minimization framework for electric vehicles

Khan

Chowdhury

et al. 2019

Computer aided Civil Eng

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This study presents the Wireless Charging Utility Maximization (WCUM) framework, which aims to maximize the utility of Wireless Charging Units (WCUs) for electric vehicle (EV) charging through the optimal WCU deployment at signalized intersections. Furthermore, the framework aims to minimize the control delay at all signalized intersections of the network. The framework consists of a two‐step optimization formulation, a dynamic traffic assignment model to calculate the user equilibrium, a traffic microsimulator to formulate the objective functions, and a global Mixed Integer Non‐Linear Programming (MINLP) optimization solver. An optimization problem is formulated for each intersection, and another for the entire network. The performance of the WCUM framework is tested using the Sioux Falls network. We perform a comparative study of 12 global MINLP solvers with a case study. Based on solution quality and computation time, we choose the Couenne solver for this framework.

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An Efficient Wireless Power Transfer System to Balance the State of Charge of Electric Vehicles

Cited by 19 publications

References 24 publications

Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach

Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach

Optimal Placement of wireless charging lanes in road networks

Wireless charging utility maximization and intersection control delay minimization framework for electric vehicles

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